[IMPORTANT] Use

TaskCreate

to break ALL work into small tasks BEFORE starting.

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Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

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AI Mistake Prevention — Failure modes to avoid on every task:

• Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.
• Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.
• Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.
• Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.
• When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.
• Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.
• Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.
• Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.
• Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.
• Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

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Quick Summary

Goal: Analyze market landscape with competitive analysis, sizing, trends, SWOT, and customer segmentation.

Workflow:

1. Define scope — Industry, geography, segment, timeframe
2. Research competitors — WebSearch for players, positioning, strengths/weaknesses
3. Size the market — TAM/SAM/SOM from industry reports
4. Identify trends — Growth drivers, disruptions, regulatory changes
5. SWOT analysis — Synthesize Strengths/Weaknesses/Opportunities/Threats
6. Segment customers — Demographics, psychographics, jobs-to-be-done

Key Rules:

• Prefer Tier 1-2 sources for market sizing
• Every market size claim must cite source + methodology
• SWOT items linked to evidence, not speculation

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Market Analysis

Step 1: Define Market Scope

Clarify with user:

• Industry/vertical — What market segment?
• Geography — Global, regional, or local?
• Timeframe — Current state? 3-year projection?
• Focus — B2B, B2C, or both?

Step 2: Competitive Research

For each competitor (identify 5-10):

Field	Source
Company name	WebSearch
Positioning/tagline	Company website
Key products	Product pages
Pricing model	Pricing page or reports
Strengths	Reviews, analyst reports
Weaknesses	Reviews, customer complaints
Market share (if available)	Industry reports

Step 3: Market Sizing

Use Tier 1-2 sources (Gartner, Statista, IBISWorld, government data):

• TAM (Total Addressable Market) — Maximum possible revenue if 100% market share
• SAM (Serviceable Addressable Market) — Portion accessible given constraints
• SOM (Serviceable Obtainable Market) — Realistic capture in 3 years

Every number must cite: source, year, methodology.

Step 4: Trend Analysis

Research and categorize:

• Growth drivers — What's fueling market growth?
• Disruptions — Technology shifts, new entrants, business model innovations
• Regulatory — New laws, compliance requirements, policy changes
• Consumer behavior — Changing preferences, demographics shifts

Step 5: SWOT Analysis

Each item must link to evidence:

Category	Item	Evidence
Strength	{item}	Source [N]
Weakness	{item}	Source [N]
Opportunity	{item}	Source [N]
Threat	{item}	Source [N]

Step 6: Customer Segmentation

For each segment:

• Demographics — Age, role, income, company size
• Psychographics — Values, pain points, aspirations
• Behavior — Buying patterns, media consumption
• Jobs-to-be-Done — What are they trying to accomplish?

Output

Market analysis is typically consumed by:

• strategy-builder

  skill (marketing strategy)

• business-evaluation

  skill (business viability)

Write findings to working file or inline with consuming skill's output.

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Closing Reminders

• IMPORTANT MUST ATTENTION break work into small todo tasks using

  TaskCreate

  BEFORE starting
• IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
• IMPORTANT MUST ATTENTION cite

  file:line

  evidence for every claim (confidence >80% to act)
• IMPORTANT MUST ATTENTION add a final review todo task to verify work quality <!-- SYNC:critical-thinking-mindset:reminder -->
• MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
• MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->